Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention

no code implementations • 21 Feb 2023 • Jiahui Wang, Haiyue Zhu, Haoren Guo, Abdullah Al Mamun, Cheng Xiang, Tong Heng Lee

Moreover, a case study on practical CAM/CAD segmentation is presented to demonstrate the effectiveness of our approach for real-world applications.

Contrastive Learning Few-Shot Learning +2

Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools

no code implementations • 4 Jul 2022 • Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad, Weng Khuen Ho, Tong Heng Lee

With the availability of deep learning approaches, the great potential and prospect of utilizing these for RUL prediction have resulted in several models which are designed driven by operation data of manufacturing machines.

Self-Supervised Learning

CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning

no code implementations • 4 Jul 2022 • Jiahui Wang, Haiyue Zhu, Haoren Guo, Abdullah Al Mamun, Vadakkepat Prahlad, Tong Heng Lee

However, the disadvantage is that the resulting models from the fully-supervised learning methodology are highly reliant on the completeness of the available dataset, and its generalization ability is relatively poor to new unknown segmentation types (i. e. further additional novel classes).

3D Part Segmentation Few-Shot Learning +1